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An industry foundation classes (IFC) web-based approach and platform for bi-drectional conversion of structural analysis models

Lookup NU author(s): Professor Mohamad Kassem

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Abstract

© ASCE 2014. Projects in the Architectural Engineering and Construction (AEC) industry involve several organizations and practitioners who are required to share a very diverse set of information and models. Building Information Modeling (BIM) and open standards, such as Industry Foundation Classes (IFC), have made substantial progress in improving the interoperability in recent years. However, inadequate interoperability is still inflicting an economic burden and is considered to be one of the main limiting factors for BIM adoption. This paper presents an IFC and Web-based approach and tool that enable a bi-directional conversion among structural analysis models. The approach consists of an IFC-based unified information model and a number of algorithms that help overcome the differences between the data structures and representation logics of different structural analysis technologies. A web-based platform that utilizes WebGL was developed to enable the sharing and converting of different building models. In a live case study, the testing of the approach and the platform developed demonstrated consistency in the conversion process and stability and rendering quality in the display of models over the Web browser.


Publication metadata

Author(s): Zhang X-Y, Hu Z-Z, Wang H-W, Kassem M

Editor(s): Raymond Issa Issa; Ian Flood

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computing in Civil and Building Engineering - Proceedings of the 2014 International Conference on Computing in Civil and Building Engineering

Year of Conference: 2014

Pages: 390-397

Online publication date: 17/06/2014

Acceptance date: 01/01/1900

Publisher: American Society of Civil Engineers (ASCE)

URL: https://doi.org/10.1061/9780784413616.049

DOI: 10.1061/9780784413616.049

Library holdings: Search Newcastle University Library for this item

ISBN: 9780784413616


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